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C-Loss Based Higher Order Fuzzy Inference Systems for Identifying DNA N4-Methylcytosine Sites

Yijie Ding, Prayag Tiwari, Quan Zou, Fei Guo, Hari Mohan Pandey

2022IEEE Transactions on Fuzzy Systems47 citationsDOIOpen Access PDF

Abstract

DNA methylation is an epigenetic marker that plays an important role in the biological processes of regulating gene expression, maintaining chromatin structure, imprinting genes, inactivating X chromosomes, and developing embryos. The traditional detection method is time-consuming. Currently, researchers have used effective computational methods to improve the efficiency of methylation detection. This study proposes a fuzzy model with correntropy induced loss (C-loss) function to identify DNA N4-methylcytosine (4 mC) sites. To improve the robustness and performance of the model, we use kernel method and the C-loss function to build a higher order fuzzy inference systems. To test performance, our model is implemented on six 4 mC and eight University of California Irvine (UCI) datasets. The experimental results show that our model achieves better prediction performance.

Topics & Concepts

Robustness (evolution)DNA methylationEpigeneticsComputer scienceFuzzy logicInferenceChromatinFuzzy inference systemArtificial intelligenceKernel (algebra)Fuzzy control systemBiologyComputational biologyMachine learningGeneGeneticsAdaptive neuro fuzzy inference systemMathematicsGene expressionCombinatoricsMachine Learning in BioinformaticsAlgorithms and Data CompressionNetwork Security and Intrusion Detection
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